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I work in the healthcare field and talk to hundreds of providers every month. I know the industry. This tool, in theory, is good. But, the most important thing about medicine is that it is practiced; one size does not fit all. That means that every patient is different. Their tolerance for pain, anguish, or whatever else ails them is different from patient to patient. This allows or disallows medical providers to choose their line of therapy tailored to the patient. This tool is a way for hospital systems to create one size fits all formularies (roadmaps of care) for every disease state.

As well, I have met many surgeons who are basically cherry-pickers. That is, they choose the easiest slam-dunk stuff to up their reputation in the field (and therefore their dollar value). They simply will not attempt that risky cancer surgery, as an example, that only has a 10% chance of saving your ass even though the alternative is not attempting anything at all and watching you die. This tool will help them avoid these risky “hail-Mary” surgeries so they can avoid all things risky. In fact, I can totally foresee hospital systems regulating possible care metric in accordance to this sort of system.

The very idea of a machine learning based system is that it isn’t “one size fits all” as you describe it. Sure, it’s only a tool. But it is one that can track a lot more variables in real time than any individual can keep track of themselves.

Absolutely it’s a good thing. I agree. But, I’ve seen things like this implemented in a way that makes a patient’s care tied to a mathematical equation - which is notoriously done in hospital systems to create formulary. There’s so much more to a patient than that. Mathematical equations ignore the reality of a patient’s lifestyle, psyche, ability to cope with disease, and on and on. Things like this are a pitfall for people with engineer brains who make management decisions at hospitals - they forget that they’re ultimately dealing with people who are all different.